Python Tutorial: Intermediate Network Analysis in Python | Definitions & basic recap

Key Takeaways

hi I'm Eric and I'm a computational biological engineer and I'll be your instructor for this course to get started let's start by recapping some definitions recall that a network which is also known as a graph is comprised of two sets a set of nodes and a set of edges we often draw graphs as circles joined by lines where the circles represent some real-world entity such as individuals in a social network and the lines denote some relationship between the entities such as being connected as friends in the social network a graph can be directed or undirected previously we saw some examples of undirected graphs such as Facebook if I request to connect with another person on Facebook once the other person accepts the friend request we immediately connect and no direction is unapplied thus it is an undirected graph on the other hand if we look at the Twitter network I may choose to follow another user but that user may not necessarily follow me back in this way the Twitter social network is a directed Network in Python there is a package called Network X which contains a library of classes and functions for the creation analysis and manipulation of graphs in the previous course we showed you some of the basics of the network X API and applied those functions to case studies let's take a quick look at the basics of the API to refresh your memory as always we must first import Network X into our Python session suppose we had a graph G that already exists in memory if I want to know how many nodes exist in that graph I can call on jeez my third nodes which will return a list of every node in the graph the analogous method edges also exists because both nodes and edges return a list it is thus possible to get the length of each of those elements Len G notes gives us the number of nodes in the graph and Len G dot edges gives us the number of edges in the graph using these two lines of code we can start describing a graphs basic statistics if you remember there were multiple types of graphs and we can check the type of the graph by doing type G which in this case is a regular graph object other graph types include digraph multi graph and multi diagraph previously you also learned about the NX vias package which is a package I wrote that provides a simple API for the visualization of large complex networks in a rational fashion rational visualizations prioritized the nodes placement this allows us to create beautiful visualizations such as the matrix plot the arc plot the circo's plot and the hive plot we will be using the circles plot the most in this course as I personally think that it has the best combination of aesthetics and functionality to use the circo's plot you must first import NX vis and matplotlib spy plot as PLT then you can instantiate a new plot object passing in the graph G after that you'll have to call the dot draw method of the plot object finally call the PLT dot show function to get the plot to be drawn to screen yielding beautiful network diagrams like the ones below once you're done with the coming warm-up exercises we'll come back to explore a new topic bipartite graphs have fun with the exercises